AI Empowering Pharmaceutical R&D | Chihealbio Ushers in a New Era of Digital-Intelligent Transformation
As an innovative enterprise deeply engaged in the pharmaceutical CRO field, Chihealbio has always been committed to providing the industry with a full range of services covering the development of innovative drugs, improved new drugs, and generic drugs. Now, in the face of the global wave of intelligent pharmaceutical R&D, Chihealbio has confidently embraced cutting-edge technology, using AI as the engine to embark on a new chapter of digital-intelligent transformation.
Recently, a team of AI PhD experts from Nanjing University was invited to visit Chihealbio, where they engaged in in-depth discussions with Dr. Ding Wei, Chief Scientist of Peptides and Director of the AI Center, and Dr. Fu Haijian, Director of the Innovative Drug Division and President of the Molecular Design Research Institute. The two sides explored the core applications of artificial intelligence in innovative drug development, including target discovery, molecular design, optimization of preclinical research, and clinical trial design, discussing the feasibility of technology implementation and future cooperation pathways.
Chairman Zhang Zhefeng and General Manager Hou Wen participated in the entire meeting. Chairman Zhang Zhefeng emphasized, "AI technology is not just a tool, but a driving force behind the paradigm shift in pharmaceutical R&D. Chihealbio will adopt an open approach, collaborating with AI teams to fully launch the all-scenario application plan for Chihealbio's AI platforms such as DeepSeek. The goal is to enhance the efficiency of innovative drug R&D, optimize development processes, seize marketing opportunities, improve management efficiency, and reduce operational costs, injecting 'digital-intelligent momentum' into pharmaceutical innovation."
1. AI Empowering Drug Development: Precision Breakthroughs from Target to Molecule
In the field of innovative drug development, the introduction of AI technology is reshaping traditional R&D models from the ground up. Chihealbio focuses on core scenarios in innovative drug development to achieve technological breakthroughs:
Intelligent Compound Screening: From "Finding a Needle in a Haystack" to "Precision Targeting"
Leveraging the DeepSeek platform, the machine learning analysis capability of large compound libraries is further enhanced to quickly identify potential active molecules. Traditional manual screening is limited by data volume and analysis dimensions, whereas AI, combined with multi-dimensional parameters such as Autodock VINA, optimizes the scoring mechanism, significantly improving the efficiency and accuracy of lead compound screening. This has led to a significant reduction in the drug discovery cycle, compressing the traditional "ten years to forge a sword" into "five years to determine the future."
By simulating the spatial conformation of target binding sites with AI, the small molecule docking model is optimized, providing a new approach for drug development. By addressing the issue of dirty data interference during the R&D process, the reliability of data generated by the simulator is improved, enhancing model training effectiveness and providing more accurate decision-making foundations for subsequent experimental designs.
As early as 2019, Chihealbio signed a strategic cooperation agreement with Macau University of Science and Technology (MUST) and Shenyang Pharmaceutical University in the field of AI-powered innovative drug development. Dr. Ding Wei was appointed as an exchange scholar to regularly visit MUST for research on AI and molecular design. Over the past three years, Chihealbio’s innovative drug team has conducted AI-based practical training activities, including the development of cap-dependent nuclease inhibitors and GLP-1 target small molecule design.
By combining variational autoencoders and reinforcement learning with deep learning neural network technology, the system first identifies, classifies, extracts, and analyzes raw data, followed by deep learning and training. It then predicts and outputs satisfactory results, mimicking the human learning process to make decisions. This enhances the accuracy of predictions, simulations, and computations in innovative drug development.
Drawing on relevant literature such as the GLP-1 agonist small molecule lead compounds and GLP-1 protein crystal structures, the deep learning model is trained and output using Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) techniques. A dedicated compound database for virtual screening is used, and computational evaluation and validation are carried out using molecular simulation software such as Schrodinger-Glide, AutoDock Vina, Discovery Studio, and rDock.
2. Large Language Model Implementation: Reshaping Corporate Management Efficiency and Innovation Power
In internal management and R&D support scenarios, Chihealbio will deeply integrate large language model technology to drive the intelligent upgrade of the entire process:
R&D Efficiency Leap: From "Manual Writing" to "AI Collaboration"
By deploying large language models locally, the R&D team’s ability to integrate pharmaceutical knowledge, clinical trial protocol design, submission documents, and data analysis reports is enhanced.
Management Process Optimization: The "Smart Assistant" for Cost Reduction and Efficiency Improvement
In daily operations, AI tools will be deeply integrated into scenarios such as meeting minutes generation, PPT creation, and cross-department collaboration. Through employee training and standardized process design, a "human-machine collaboration" model for efficient office work will be gradually built, reducing repetitive tasks and unleashing the team's creativity.
Ecosystem Cooperation and Transformation: Moving Towards the "AI + Pharmaceutical" Platform
The company has reserved multiple potential product varieties and is actively exploring deep cooperation models with pharmaceutical companies, B-certification enterprises, sales companies, and research institutions. In the future, Chihealbio will drive its transformation into an innovative pharmaceutical enterprise through a "technology + service" dual-engine approach, building an AI-powered ecosystem covering R&D, production, and sales.
Chihealbio firmly believes that technological innovation is the core driving force for high-quality development in the pharmaceutical industry. Through the deep application of the DeepSeek platform, we have not only achieved a leap in R&D efficiency but also made initial strides in building the "AI + Pharmaceutical" ecosystem at the strategic level. Chihealbio is accelerating its transformation from a traditional CRO to a leader in the "AI + Pharmaceutical" ecosystem. In the future, we will continue to explore the boundaries of AI integration with pharmaceutical R&D, providing smarter solutions to help our clients break through technological barriers and jointly write the next decade of pharmaceutical innovation!
